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- Progressive Growing GAN Description: The 'Progressive Growing GAN' is a type of Generative Adversarial Network characterized by its innovative approach to training(...) Read more
- PatchGAN Description: PatchGAN is a Generative Adversarial Network (GAN) architecture that focuses on classifying image patches rather than evaluating(...) Read more
- Parameter sharing Description: Parameter sharing is a technique used in the field of large language models (LLMs) that involves using the same parameters across(...) Read more
- Pre-trained model Description: A pre-trained model is a type of machine learning model that has been previously trained on a massive dataset before being(...) Read more
- Pixel normalization Description: Pixel normalization is the process of adjusting pixel values to a common scale, allowing images to be more consistent and(...) Read more
- Projection Discriminator Description: The Projection Discriminator is a key component in Generative Adversarial Networks (GANs), designed to evaluate the authenticity of(...) Read more
- Pyramid Pooling Description: Pyramid pooling is a technique that uses multiple pooling layers at different scales to capture spatial information. This(...) Read more
- Perceptual Similarity Description: Perceptual similarity is a measure that evaluates how similar two images appear to a human observer. This concept is fundamental in(...) Read more
- PixelCNN Description: PixelCNN is a generative model that uses convolutional neural networks to model the pixel distribution in images. Unlike other(...) Read more
- Pseudorandom Noise Description: Pseudorandom noise is a type of noise generated by deterministic algorithms that simulate randomness. Unlike truly random noise,(...) Read more
- Pixel-wise Accuracy Description: Pixel Accuracy is a fundamental metric in the field of Generative Adversarial Networks (GANs), used to evaluate the quality of(...) Read more
- Pyramid Structure Description: The pyramidal structure is a hierarchical approach used in some architectures of Generative Adversarial Networks (GANs) to process(...) Read more
- Prior Knowledge Description: Prior knowledge in the context of Generative Adversarial Networks (GANs) refers to information that can be used to inform the(...) Read more
- Phase Shift Description: Phase shifting is a technique used in some architectures of Generative Adversarial Networks (GANs) that aims to enhance feature(...) Read more
- Parallel Training Description: Parallel training is a method used in the field of machine learning, specifically in Generative Adversarial Networks (GANs), where(...) Read more
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